In order to protect the lives of passengers during a traffic accident, modern vehicles are generally fitted with a protection system comprising several airbags and seat belt pretensioners, which are used to absorb the energy of a passenger released during the collision due to the accident. It is clear that such systems are even more effective when they are better adapted to the specific requirements of each passenger, i.e. to the weight and/or the size of the passenger. That is why microprocessor-controlled protection systems have been designed which provide several operational modes, allowing for example an adaptation of the instant at which airbags are deployed, the volume to which the airbags are inflated, the instant at which safety belts are released after the collision, etc, as a function of the stature of the passenger and the orientation of the passenger on the seat.
In order to enable the control microprocessor to select the optimum operational mode for a given seat occupancy status, it is therefore necessary to detect one or several parameters characterizing the occupancy status of the seat and to classify the occupancy into one of several classes, each of which is associated to a specific operational mode of the restraint system.
The detection of the occupancy parameters is commonly achieved by seat occupancy sensors, which comprise a plurality of pressure sensors distributed over the surface of the seat. The pressure sensors comprise pressure sensitive resistors, i.e. the resistance of these pressure sensors changes with the pressure applied on the sensor. The reading of the resistance values of the individual pressure sensors thus gives an indication on the pressure acting on each cell and accordingly can be related to the weight acting on the seat. Furthermore the distribution of the pressure values over the surface of the seat can be related to the size or the form of a person or an object occupying the seat.
In a very simple method for controlling the restraint system, the occupancy status is repeatedly monitored by means of one or more specific parameters of the occupancy detector, and an actual occupancy class is associated to the measured parameter. This actual occupancy class is then directly used by the microprocessor for selecting the adequate operational mode of the restraint system. Unfortunately a passenger often changes its position on the seat, thereby shifting its weight respectively its center of weight. Each movement will change the readings on the different pressure sensors so that the classification will vary arbitrarily with time.
In order to dampen the arbitrary variations of the classification, the actual class parameter can be stored into a buffer comprising several previously determined classes and a filtered class can be set to the average value of the individual stored classes. While such a filtering provides an improved classification result, this method is still not reliable enough.
Other methods are based on an evaluation of the quality of the actually recorded pressure profile of the occupancy sensor. In these methods, the actually determined class resp. the actually determined parameters are used for the determination of a filtered class only if the profile quality exceeds a specific threshold. A method of this kind is e.g. disclosed in WO99/38731. With such a method, the accuracy of the classification increases with time such that after a certain time following the system reset during ignition of the car, the control module of a secondary restraint system will be fed with a high accuracy parameter, enabling the selection of an optimum deployment modus for the present occupancy status.
However during the initialization period, i.e. immediately following the ignition of the engine, the classification of the actual occupancy status may be rather inaccurate due to the reduced number of recorded and evaluated profiles. This problem is aggravated, if the passenger does not take an optimal position on the seat, which would permit to record high quality profiles.